Prediction and Elimination of Physiological Tremor During Control of Teleoperated Robot Based on Deep Learning by Juntao Chen, Zhiqing Zhang, Wei Guan, Xinxin Cao, Ke Liang

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Comparative Analysis of Machine Learning Algorithms With Advanced Feature Extraction for ECG Signal Classification by Tanuja Subba, Tejbanta Chingtham

“…The work discusses the importance of automated classification techniques that make it possible to analyze vast amounts of ECG data effectively and objectively. This research presents an investigation into the classification of ECG signals using various Machine Learning (ML) methods. …”
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Enhanced Brain Tumor Segmentation Using CBAM-Integrated Deep Learning and Area Quantification by Rafiqul Islam, Sazzad Hossain

“…Consequently, automated approaches are anticipated to accurately delineate tumor boundaries and quantify tumor burden, addressing these challenges efficiently. The presented work integrates a convolutional block attention module (CBAM) into a deep learning architecture to enhance the accuracy of MRI-based brain tumor segmentation. …”
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Dense Segmentation Techniques Using Deep Learning for Urban Scene Parsing: A Review by Rajesh Ankareddy, Radhakrishnan Delhibabu

“…This paper examines various deep learning methodologies to enhance dense segmentation in urban scene parsing. …”
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AGE AND GENDER CLASSIFICATION FROM IRIS IMAGES OF THE EYE USING MACHINE LEARNING TECHNIQUES by Martins E. Irhebhude, Adeola O. Kolawole, Halima Abemi

“…The human face stands out as a preferable choice for biometric human authentication, the iris is a secure biometric that contains features with a low forgery rate and is unique to individuals. This paper presents a model for age and gender classification from iris images captured from male and female genders between the ages of 5 and 60 years. …”
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The Application of the Approach of “Cognitive Structure” in the Teaching Methods of the Holy Quran in Respect to Meaningful Learning by Zahra Safian Jozdani, Reza Saadat Nia

“…The present research with paying attention to the importance and impact of the stability of the cognitive structure in the area of the teaching fields has been organized. …”
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Pothole Detection Using Deep Learning: A Real-Time and AI-on-the-Edge Perspective by Muhammad Haroon Asad, Saran Khaliq, Muhammad Haroon Yousaf, Muhammad Obaid Ullah, Afaq Ahmad

“…Detailed real-time performance comparison of state-of-the-art deep learning models and object detection frameworks (YOLOv1, YOLOv2, YOLOv3, YOLOv4, Tiny-YOLOv4, YOLOv5, and SSD-mobilenetv2) for pothole detection is presented. …”
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Semi-supervised action recognition using logit aligned consistency and adaptive negative learning by Fengyun Zuo, Yang Xu, Minggang Wang

“…Furthermore, we incorporate the Adaptive Negative Learning (ANL) method to introduce additional negative pseudo-labels, which dynamically evaluate the Top-k performance of the model to adaptively assign negative labels, thus making better use of ambiguous prediction examples. …”
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Effectiveness of machine learning methods in detecting grooming: a systematic meta-analytic review by Marcelo Leiva-Bianchi, Nicolas Castillo, César A. Astudillo, Francisco Ahumada-Méndez

“…Abstract This study presents a systematic review (SR) and meta-analysis (MA) on the use of machine learning (ML) methods for detecting online grooming, a form of manipulation and child sexual abuse. …”
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Peer Learning Has Double Effects in Clinical Research Education: A Qualitative Study by Hiro Nakao, Osamu Nomura, Chie Nagata, Akira Ishiguro

“…Background. Peer learning has been recognized for its effectiveness in health professional education. …”
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A comparative study of deep learning approaches for real-time solar irradiance forecasting by Fennane Sara, Kacimi Houda, Mabchour Hamza, ALtalqi Fatehi, El Massaoudi El Mahdi, Echchelh Adil

“…A comparative assessment of several deep learning models is presented in this study for real-time GHI forecasting, specifically Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU), and a hybrid LSTM-GRU architecture. …”
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Enhancing Invoice Processing Automation Through the Integration of DevOps Methodologies and Machine Learning by Oana-Alexandra Dragomirescu, Pavel-Cristian Crăciun, Ana Ramona Bologa

“…Traditional methods of invoice management, which are heavily reliant on manual labor, not only incur significant costs but also contribute to inefficiencies, delays, and resource wastage. This article presents an integrated framework that combines DevOps methodologies and machine learning (ML) to transform invoice processing into a scalable and sustainable operation. …”
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Web application using machine learning to predict cardiovascular disease and hypertension in mine workers by Sohrab Effati, Alireza Kamarzardi-Torghabe, Fatemeh Azizi-Froutaghe, Iman Atighi, Somayeh Ghiasi-Hafez

“…Abstract This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. …”
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Predicting Mobile Payment Behavior Through Explainable Machine Learning and Application Usage Analysis by Myounggu Lee, Insu Choi, Woo-Chang Kim

“…To address the complexity of the data, we use a combination of machine-learning models, including extreme gradient boosting, light gradient boosting machine, and CatBoost, along with Shapley additive explanations (SHAP) to improve interpretability. …”
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Advancing sustainable investing: A deep learning model for multi-source stock prediction by Hongxuan Yu, Tingting Zhang, Murat Kizildag

“…Stock price fluctuations, influenced by many factors, including company fundamentals, market sentiment, capital flows, industry news, and macroeconomic policies, present a highly dynamic and complex challenge for predictive modeling. …”
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MACHINE LEARNING BASED STRATEGY FOR MITM ATTACK MITIGATION UTILIZING HYBRID FEATURE SELECTION by Pratik Kumar Swain, Suneeta Satpathy, Srinivasa Rao Pokuri

“…This study integrates machine learning classification, dimensionality reduction, and hybrid feature selection to present a novel approach for MITM threat identification. …”
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Research Trends in Project-Based Learning in Elementary Schools (2001-2024): Bibliometric Analysis by Purwandari Purwandari, Farida Huriawati, Viola Dea Amanda Sarry, Ita Susanti

“… Project-Based Learning (PjBL) is an educational method that engages students in completing projects relevant to real-life contexts, fostering critical thinking and problem-solving skills. …”
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Data-driven evaluation of background radiation safety using machine learning and statistical analysis by Muhammad Abid, Muhammad Shahid

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Machine Learning Model Optimization for Antarctic Blowing Snow Height and Optical Depth Diagnosis by Surendra Bhatta, Yuekui Yang

“…Previous research developed an optimized machine learning (ML) model to diagnose blowing snow occurrence using meteorological fields from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). …”
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A comprehensive deep learning approach to improve enchondroma detection on X-ray images by Ayhan Aydin, Caner Ozcan, Safak Aydın Simsek, Ferhat Say

“…This study aimed to identify and present cases of bone tissue enchondromas to field specialists as preliminary data. …”
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